The fields of computer science and game theory both trace their roots to the first half of the 20th century, with the work of Turing, von Neumann, Nash, and others. Fast forwarding to the present, there are now many fruitful points of contact between these two fields. Game theory plays an important role in 21st-century computer science applications, ranging from social networks to routing in the Internet. The flow of ideas also travels in the other direction, with computer science offering a number of tools to reason about economic problems in novel ways. For example, computational complexity theory sheds new light on the “bounded rationality” of decision-makers. Approximation guarantees, originally developed to analyse fast heuristic algorithms, can be usefully applied to Nash equilibria. Computationally efficient algorithms are an essential ingredient to modern, large-scale auction designs. In this lecture, Tim Roughgarden will survey the key ideas behind these connections and their implications.

Tim Roughgarden is a Professor in the Computer Science and (by courtesy) Management Science and Engineering Departments, Stanford University, as well as a Visiting Professor in the Department of Mathematics at LSE.

Martin Anthony (@MartinHGAnthony) is Professor of Mathematics and Head of Department of Mathematics at LSE.

The Department of Mathematics (@LSEMaths) is internationally recognised for its teaching and research in the fields of discrete mathematics, game theory, financial mathematics and operations research.

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